American Recovery and Reinvestment Act Investments in Data Infrastructure
Download
Key Findings
- More than half of the projects proposed to build infrastructure or address research questions specific to one or more medical conditions, including cardiovascular diseases and cancer.
- At the time of the study, projects were making strong progress toward meeting goals, which included automating data collection and aggregating data from multiple data sources, developing databases and data sets that incorporated data from various sources and were large enough that projects could address questions specific to the Institute of Medicine priority populations, successfully integrating informatics tools and algorithms into electronic health records for clinical use and for conducting CER, expanding existing research networks, and conducting pilot tests.
- Project investigators reported several facilitators of project success, including an existing infrastructure to build upon, a project team with relevant expertise, and strong partner collaborations.
- Investigators mentioned lacking an existing project infrastructure to build upon, experienced team members, and partner buy-in as challenges to their project’s success. In addition, they described challenges in linking data from different systems, data completeness, and consistency problems and regulatory issues.
Aim
This article describes American Reinvestment and Recovery Act comparative effectiveness research (CER) data infrastructure (DI) investments and identifies facilitators and barriers to implementation.
Materials and Methods
We reviewed original project proposals, conducted an investigator survey, and interviewed project officers and principal investigators.
Results
DI projects assembled or enhanced existing clinical data sets, established linkages between public and private data sources, and built infrastructure. Facilitators included building on existing relationships across organizations and making collection as seamless as possible for clinicians.
Conclusion
To sustain DI, investigators should reduce the burden of CER data collection on practices, adequately address data privacy and security issues, resolve or lessen the impact of data-linking issues, and build research capacity for other investigators and clinicians.
More like this from Mathematica
Featured Publication
Evaluation of the Maryland Total Cost of Care Model: Progress Report
How do you apply evidence?
Take our quick four-question survey to help us curate evidence and insights that serve you.
Take our survey